Modeling and Analysis of Stock Sharing and Postponement Strategies in Regional Humanitarian Aid Networks

Prepositioning of emergency supplies in warehouses in the humanitarian aid network is a disaster preparedness strategy widely applied by humanitarian organizations (HO). Prepositioning allows humanitarian organizations to ship the relief supplies to the disaster affected areas quickly. However, pre-positioning can be a costly investment for humanitarian organizations. In this project, we investigate a stock-sharing based collaborative strategy, which can improve the effective usage of prepositioned stocks of the humanitarian organizations while reducing inventory costs. Currently, HOs keep their pre-positioning stocks in warehouses generally ready for shipment as final products (packed and branded). When relief materials stored in warehouses in such a final product form are shared with other HOs after the disaster, the materials must be repackaged and rebranded. Therefore, the branded stocks are usually not shared among the HOs. In the proposed collaborative system, the product postponement strategy is used to keep some of the relief materials in an unbranded form (i.e., standard form). By sharing the stocks held in the standard form among the HOs, more effective response performance can be achieved. In the literature, there is no study on the application of the product postponement strategy in humanitarian supply chains. This project focuses on a regional aid network comprising of several HOs who preposition relief items in the same depots that are located in the network. The project aims to: i) evaluate the impact of the proposed collaboration based on stock sharing and product postponement strategies on pre-positioning costs and disaster response performance of HOs and ii) develop analytical methods for the effective implementation of stock-sharing and postponing strategies. To achieve these objectives, a Monte Carlo simulation algorithm and a two-stage stochastic programming model are developed. The proposed methods are tested on a realistic regional network and solutions are analyzed. The implementation of the simulation algorithm shows the effects of different stock sharing policies and postponement levels on different performance metrics. The results show that the proposed collaboration strategy can improve response levels and response times, as well as the utilization of prepositioned stocks. The results of the two-stage stochastic programming, which is developed to determine the number of standard products that will be held by different HOs in the regional warehouse and the amount of stock held by each agency in each warehouse, also show that the proposed collaborative system improves country-based performance metrics and leads HOs to use their inventory more effectively.